Weekly Roadmap*

1. Getting started with R and RStudio
2. Plotting with {ggplot2}
3. Importing and transforming data
4. Exploratory data analysis
5. Interactive and animated plots
6. Mapping (will work in relational data)
7. Text mining
8. Flexdashboards (and shiny apps)
9. Tidymodels
10. Reproducible workflows

* subject to change

Today’s plan

• Review tips for thinking about exploratory data analysis
• Learn some common first steps for summarizing and visualizing data while getting some practice with {dplyr}
• RMarkdown goal: output to APA-style manuscript with {papaja} package

Today’s plot inspiration

Kieran Healy, {covdata} package, https://kjhealy.github.io/covdata/

Today’s plot goal

Last week: Importing Data

• Local files
  • csv: read.csv()
  • RData: load()
  • Stata: haven::read_dta()
  • SPSS: haven::read_sav()
  • SAS: haven::read_sas()
• Web
  • csv: read.csv(INSERT URL HERE)
  • Google Sheets: googlesheets4::read_sheet()
  • APIs with {httr} and {jsonlite}
  • web scraping with {rvest}

Last week: dplyr

https://dplyr.tidyverse.org/

Exploratory Data Analysis

https://leanpub.com/exdata

Peng’s EDA Checklist

Roger Peng, https://tinyurl.com/y833jdgv

Tidy Tuesday Videos

David Robinson, https://youtu.be/-5HYdBq_PTM

RStudio

References